TY - RPRT
T1 - How Do People Form Longevity Predictions? The Effect of Parents and Parents-in-law s Death on Beliefs about Mortality Risk
Y1 - 2013
A1 - Chen, Lizi
A1 - Economics
KW - Health Conditions and Status
KW - Healthcare
KW - Methodology
KW - Retirement Planning and Satisfaction
AB - In this paper, we use data from the Health and Retirement Study (HRS) panel, which surveys a representative sample of US seniors about their longevity prospects to examine whether the Bayesian assumption holds. Specifically, I test for (1) whether people s longevity predictions are responsive to new information, e.g., recent parental death which conveys information about genetic risks, lifestyle-related health risks, etc; (2) whether people s longevity predictions respond more to the arrival of precise information (parental death) than less clear information (parent-in-law s death); (3) whether the magnitudes of these updates are in accordance with theoretical predictions. We find that individuals longevity predictions are responsive to new health-related information, and consistently more responsive to precise information (parental death) than imprecise information (parent-in-law s death). The magnitudes of these updates lie between the predicted lower and upper bounds of rational updates, but do not perfectly coincide with the predicted values and are sensitive to model specifications. We conclude that there is no strong evidence against the Bayesian assumption. We point out that the Bayesian assumption is only one aspect of the rationality hypothesis. From qualitative survey data, We find evidence of inattention to government subsidy of long-term care insurance, mistaken beliefs that long-term care is covered by Medicare and tendency to procrastinate on long-term care insurance purchasing decision. The evidence suggests irrationality may cause individuals to under-insure through these other venues.
PB - Wellesley, MA, Wellesley College
UR - http://repository.wellesley.edu/thesiscollection/93
U4 - Bayesian Analysis/longevity predictions/Long Term Care/retirement planning/health risk
ER -